Director I, Catastrophe Modeling

Ryan Specialty•Chicago, IL

8d•$116,000 - $145,000

About The Position

The Director I of Catastrophe Modeling leads catastrophe risk analytics for the Central Underwriting organization, sitting at the intersection of modeling science, data engineering, and underwriting strategy. This role owns both the technical execution of cat modeling (RMS, AIR) and the tooling, pipelines, and automation that make that modeling fast, accurate, and scalable — while building and managing the team that delivers it. The Director translates portfolio-level model output into underwriting guidance, sets technical standards for the function, and represents catastrophe risk analytics to underwriting and executive leadership.

Requirements

8+ years of progressive experience in catastrophe modeling, portfolio risk analytics, or cat-modeling-adjacent data engineering, including prior people leadership or team-lead experience managing other modeling professionals or managers.
Deep hands-on proficiency in RMS and/or AIR Touchstone — exposure preparation, batch processing, results extraction, and interpretation of EP curves and loss tables.
Strong SQL skills and demonstrated experience directing or building automation with Python, R, VBA, and/or Alteryx.
Track record of translating catastrophe model output into underwriting or portfolio management decisions.
Proven ability to lead teams through real-time catastrophe event response.
Experience coordinating portfolio rollups and external deliverables to carriers or reinsurance partners.
Demonstrated experience partnering cross-functionally with groups such as Capital Management, Pricing, Reserving, or Data Engineering.
Excellent communication skills, with experience presenting technical analysis to underwriting and executive stakeholders.

Nice To Haves

Experience with Analyze Re or comparable portfolio roll-up/aggregation platforms.
Experience with Azure Databricks, PySpark, and Delta Lake / data lakehouse patterns.
Knowledge of reinsurance structures and portfolio risk metrics (PML, AAL, TVaR).
Familiarity with geospatial data handling and mapping (geopandas, shapefiles, spatial joins).
Experience with version control (Git) and SDLC practices (branching, code review, release management).
Prior experience leading vendor evaluations for modeling platforms, peril models, or analytics infrastructure.
Background in or exposure to applied research within catastrophe modeling or a related quantitative discipline.

Responsibilities

Build, manage, and mentor a team blending catastrophe modeling analysts and technical/automation developers.
Mentor, guide, and train portfolio modeling managers across the team, building bench strength and consistent technical standards for the broader cat modeling function.
Set the technical roadmap and priorities for cat modeling, data engineering, and reporting tooling in support of Central Underwriting.
Serve as the primary bridge between catastrophe modeling analytics and underwriting leadership, translating model output into underwriting guidance and appetite decisions.
Represent catastrophe risk analytics in executive and reinsurance discussions, including cat event response briefings.
Coordinate Analyze Re-related portfolio rollups, ensuring consistent, accurate aggregation across books of business.
Oversee delivery of portfolio and modeling outputs to external carriers and reinsurance partners, ensuring accuracy, timeliness, and consistency of format.
Partner with reinsurance and ceded-re contacts to align rollup structures and delivery cadence with treaty and program needs.
Lead research initiatives that extend advanced analytics capabilities within the catastrophe modeling domain (e.g., secondary uncertainty, model blending, climate-adjusted view of risk).
Evaluate emerging modeling science, vendor model updates, and academic/industry research for applicability to the portfolio.
Champion a culture of continuous improvement, piloting new methods and tools ahead of enterprise-wide adoption.
Partner closely with Capital Management, Pricing, Reserving, and Data Engineering to streamline processes and align catastrophe outputs with capital, pricing, and reserving needs.
Standardize handoffs and data contracts between cat modeling and these partner teams to reduce rework and improve turnaround.
Own vendor and platform strategy for RMS and AIR, including licensing, upgrades, and platform roadmap decisions.
Lead evaluation and assessment of tools and vendors for specific perils, models, and IT infrastructure, including Analyze Re and emerging modeling platforms.
Build the business case for new tooling or vendor changes, balancing analytical capability, cost, and infrastructure fit.
Oversee catastrophe modeling using RMS and AIR across multiple lines of business, ensuring quality and consistency of account, portfolio, and reinsurance-layer analyses.
Direct the production of portfolio-level metrics — PML, AAL, exposed limits, EP curves (OEP/AEP), and tail-risk/TVaR measures — used in underwriting and reinsurance decisions.
Set standards for exposure data preparation, validation, and cleansing prior to model runs.
Lead catastrophe event response for the underwriting organization, ensuring rapid, accurate exposure summaries and loss estimates.
Direct the design of ETL pipelines and data pipelines that ingest and normalize exposure data (policy schedules, CRE, shapefiles) to RMS/AIR data standards.
Oversee development of automated AIR/RMS workflow utilities (imports/exports, batch runs, result extraction, QA checks) and reusable reporting assets in SQL, Python, R, and Excel/VBA.
Champion adoption of Azure Databricks and cloud-based analytics (PySpark, Delta Lake) as the future-state platform for modeling data and results.
Ensure data quality controls, QA dashboards, and documentation/SOPs are in place and consistently followed across the team.